917 results about "Web technology" patented technology

The present invention discloses an artificial intelligence-based adaptive big data storage and retrieval optimization system and method designed to intelligently manage and optimize large-scale distributed data environments. The system integrates data acquisition, distributed storage, metadata processing, adaptive learning, and retrieval optimization units configured to work collaboratively for continuous self-optimization. The invention employs deep reinforcement learning and predictive neural network techniques to dynamically analyze system telemetry, workload behavior, and data access patterns in real time, enabling proactive adjustment of data placement, caching, replication, and compression parameters across distributed nodes. The metadata processing framework utilizes graph-based dependency modeling to maintain semantic and contextual relationships among datasets, facilitating intelligent and context-aware data retrieval. The retrieval optimization unit interprets user queries semantically and computes the optimal retrieval route using latency prediction models and dynamic routing techniques.

The invention discloses a QoS guarantee method and system for a communication network, and relates to the technical field of communication networks, and the method comprises the steps: collecting and preprocessing network state data, and forming a standardized data set; dynamically classifying service types based on an improved random forest algorithm, and predicting a future QoS demand trend of each priority service in combination with an LSTM neural network; establishing a mapping model of QoS demands and resource parameters, converting predicted demands into allocable resource indexes, monitoring the resource utilization rate in real time, and setting an elastic reservation mechanism and conflict early warning; when early warning is triggered, selecting an optimal transmission link by adopting a multi-path collaborative algorithm, and implementing differentiated resource allocation according to service priorities; and a closed-loop feedback mechanism is triggered to dynamically adjust resource allocation by monitoring the deviation between the actual QoS and a predicted value in real time. The method has the advantages that through multi-dimensional perception, LSTM prediction, dynamic resource management and multi-path scheduling, QoS requirements of services with different priorities are accurately matched, and dynamic changes of the network are efficiently coped with.

The invention provides an Internet of Vehicles vulnerability management method, system, device and medium based on a block chain, and relates to the technical field of vehicle networks, the method can comprehensively identify potential safety risks of vehicles through a dynamic and static combined vulnerability detection mechanism, and generates a structured vulnerability report; hash abstract chaining evidence storage is performed on key data of reports and subsequent repair links by using a block chain, so that the whole process of vulnerability discovery, analysis and repair is ensured not to be tampered and traceable, and the authenticity and credibility of data are improved; the integrity of the report is verified at the cloud end, and an AI analysis engine is combined to associate a CVE database and threat intelligence, so that intelligent generation and decision support of a repair scheme are realized; the hash abstract on the chain of the OTA patch is verified at the vehicle end, so that the credibility of the patch source and the integrity of the content are guaranteed; and finally, through feedback of an installation result and secondary uplink archiving, complete closed-loop management from vulnerability discovery to repair verification is formed.

The invention relates to the technical field of communication networks, in particular to a dynamic resource allocation method and system for an industrial 5G network. The method comprises the following steps: acquiring industrial terminal data; identifying network congestion nodes based on industrial terminal data; detecting a link congestion fault according to the network congestion node, and determining a bandwidth utilization rate; allocating spectrum resources based on the bandwidth utilization rate; performing frequency spectrum slicing on the frequency spectrum resources, and determining a flow load amount; adjusting load balance according to the traffic load, and generating a load resource report; dynamically adjusting time slot allocation by using a load resource report, and determining a task priority; task scheduling simulation is executed according to the task priority, and if congestion occurs, a congestion snapshot is stored; reducing scheduling conflicts according to the congestion snapshots, releasing bandwidth resources, and determining available network slice capacity; power resources are dynamically adjusted based on available network slice capacity. The bandwidth utilization rate and the task scheduling efficiency of the industrial 5G network are improved based on the communication network technology.

The invention discloses a complex environment information acquisition method based on a sensor network, and relates to the technical field of sensor networks, and the method comprises the steps: building a complex environment portrait and a service level, and generating a scene configuration comprising an information freshness budget, a risk heat map and an alarm threshold; based on scene configuration, configuring mesh wireless networking, time synchronization parameters and candidate relays, and constructing observation configuration and quality rules; and generating a data stream and a real-time queue state according to a self-adaptive sampling strategy and an event mark, calculating an emergency degree and distributing a forwarding probability according to an information freshness budget by combining a candidate relay and a risk heat map, outputting uploaded data and a quality record, completing convergence and grading alarm according to an alarm threshold, and generating a disposal feedback and audit index. The state set, the uncertainty set, the link idle degree and the energy sufficiency are linked under the constraint of the information freshness budget, so that hot spot encryption, low-risk sparseness, reduction of energy consumption and conflict rate and standard observation time efficiency are realized.

The invention relates to the technical field of communication networks, in particular to a resource allocation system and method in a satellite-ground fusion network, and the system comprises a satellite-ground topology and channel evolution predictor which is used for obtaining satellite ephemeris, user GNSS positioning and moving vectors, ground base station topology and a real-time CQI / RSRP measurement report; generating future link state information; the business QoE impact and switching cost modeling device is used for calculating transient interruption time of a switching action; generating switching cost information; the continuity risk quantification engine is used for generating continuity risk information containing the link maintaining risk probability, the instantaneous impact collapse probability and the link switching risk probability; the risk evasion type resource decision-making device is used for calculating maintenance link comprehensive cost and switching link comprehensive cost; calculating a dynamic switching damping threshold value; generating risk avoidance decision information; according to the invention, the high-frequency ping-pong switching near the edge state point is effectively inhibited, and the signaling overhead caused by invalid switching is reduced.

The invention relates to the technical field of industrial communication networks, in particular to a method for quickly forwarding messages from a PCIE (Peripheral Component Interface Express) interface to a WIA (Wireless Interface Architecture) interface, which comprises the following steps of: simultaneously receiving PCIE messages and WIA-FA protocol messages through a hardware logic circuit; analyzing the message in a data link layer to obtain an analysis result comprising data load and address information; packaging the analysis result according to a pre-configuration rule to generate a data frame conforming to a target protocol; and constructing a sending descriptor for the generated data frame, and sending the data frame from a corresponding interface through a direct memory access mechanism. According to the method, parallel analysis and protocol conversion of messages are achieved through a hardware logic circuit, fast address conversion is achieved through a pre-configured address mapping table, and zero-copy data transmission is achieved through a direct memory access mechanism. According to the invention, software protocol stack processing is replaced by a hardware processing flow, so that communication delay and CPU resource consumption are effectively reduced.

The invention discloses a network-on-chip routing method and device, routing nodes, equipment, a medium and a product, and relates to the technical field of network-on-chip, and the method comprises the steps: firstly, screening the routing nodes through employing the input direction of a message, and limiting the selection range of the next-hop routing node; the relative position of the target routing node relative to the current routing node is determined, the routing nodes are further screened according to the relative position, and candidate routing nodes are determined; and determining a next-hop routing node according to the cache capacity and the input direction of the candidate routing node, and transmitting the message to be transmitted to the next-hop routing node to complete routing. The problem that the routing of the network-on-chip is easy to cause network message blockage or link failure of the network-on-chip can be solved. According to the method, an input direction is adopted to limit a selection range of a next-hop routing node, a relative position is adopted to determine candidate routing nodes, the next-hop routing node is determined in the candidate routing nodes based on cache capacity, and self-adaptive deadlock-free routing is realized.

The invention provides a tunnel three-dimensional geologic body modeling method and system based on in-hole camera shooting and while-drilling lithology perception, and relates to the technical field of tunnel and underground engineering and intelligent geological information processing.The method comprises the steps that firstly, a drill hole wall optical image sequence and while-drilling engineering parameters are synchronously collected and preprocessed respectively; then establishing a depth-time mapping relation to realize accurate alignment of the multi-source data in a depth domain; then fracture intelligent identification and parameter extraction are realized through an improved U-Net network, and lithology classification is completed by using an XGBoost model; feature level and decision level fusion is carried out on the fracture features and the lithologic features, and rock mass quality grades are generated; and finally, constructing an integrated geologic model fusing lithologic distribution and a three-dimensional fracture network by adopting an implicit modeling and discrete fracture network technology. According to the method, the problem of splitting of in-hole visual information and while-drilling physical information is solved, automation and precision of geological recognition are improved, and reliable geological information support is provided for tunnel construction safety and support design.

The invention relates to the technical field of computer networks, in particular to a webpage project construction and access control method, which comprises the following steps: acquiring a Web project source code file, packaging the Web project source code file, configuring a root directory to correspond to the action of a rendering page, and generating a packaged resource file; uploading the packaged resource file to a code warehouse for code hosting, triggering an assembly line execution process, and storing the packaged resource file in a workpiece generated in the assembly line execution process; receiving an access request of a user, and determining item positioning information through a unique identifier in the access request; verifying the user access authority; if the user permission state indicates that the user permission verification is passed, requesting a corresponding resource file from a workpiece, and generating rendering page information containing API basic address information; and sending the rendering page information to a browser for page rendering.

The invention discloses an ad hoc network resource scheduling method based on selection cooperation, and belongs to the technical field of wireless ad hoc network communication networks. According to the invention, business information statistics and convergence are periodically carried out at a network node, and business applications are converged to a cluster head; the cluster head gathers whole-network service applications, calculates time slot allocation information according to service application information, then issues the whole-network time slot allocation information to the whole network in a unified manner through cooperative communication, and finally forms a time slot allocation result of the nodes through distributed calculation of the nodes of the whole network. According to the method, whether the cooperative communication mode is adopted for service and signaling transmission or not can be selected according to needs, energy consumption caused by node forwarding is reduced, and the problems that in cooperative communication, node energy consumption is high, signaling overhead is large, and the transmission rate cannot be self-adapted can be solved.

The embodiment of the invention provides a network attack detection method and device, and relates to the technical field of network, and the method comprises the steps: carrying out the attack detection of a to-be-detected message based on a feature library, and obtaining a first detection result, and the feature library comprises the message features of a known network attack; if the first detection result represents that the to-be-detected message is not an attack message, calling a pre-trained attack detection model to carry out attack detection on the to-be-detected message to obtain a second detection result; and if the second detection result represents that the to-be-detected message is an attack message, updating the feature library according to the message features of the to-be-detected message. By applying the network attack detection scheme provided by the embodiment of the invention, the network attack can be accurately detected.

The invention relates to the technical field of wireless communication networks, in particular to a vehicle-mounted multi-device Bluetooth communication cooperative management system, which comprises a connection priority scheduling module, a dynamic channel allocation module, an interference suppression optimization module, a load balancing adjustment module and a frequency switching coordination module. According to the invention, through extracting the device connection state and the communication requirement, comparing the communication priority in real time, improving the connection scheduling efficiency, and dynamically adjusting the bandwidth and the power in combination with the load and the channel occupation, the channel is prevented from being occupied by a single device for a long time, the channel utilization rate is improved, the interference abnormal device combination is rapidly identified when the interference occurs, and the interference suppression is executed; the method is advantaged in that interruption caused by signal conflicts is reduced, flow redistribution is carried out on high-load equipment through load analysis, uneven communication pressure is alleviated, a frequency switching path is optimized, delay and interruption caused by unreasonable switching are reduced, stable connection, resource balance and interference suppression under multi-equipment concurrent communication are realized, and communication efficiency is improved.

The invention discloses a cloud edge cooperative multi-channel converged communication control method and system, belongs to the technical field of wireless communication networks, and aims to improve the high efficiency, reliability and real-time performance of multi-channel converged communication in a complex scene. The method specifically comprises the following steps: constructing a hierarchical collaborative architecture of a cloud end and an edge end; the edge end collects network state parameters of various communication channels, outputs a channel quality evaluation value based on a time sequence prediction model, and performs multi-channel data transmission through an extended communication protocol when triggering channel switching; the edge end executes network parameter configuration, flow priority scheduling and running state data acquisition operation, and the cloud end generates a soft routing optimization instruction based on running state data and issues the soft routing optimization instruction to the edge end to execute and adjust network transmission performance parameters; and monitoring the container operation state and the equipment state of the edge end in real time, when a monitoring result is matched with a preset abnormal rule, generating alarm information by the edge end, returning the alarm information to the cloud end to generate a global security policy, and issuing the global security policy to the edge end to update the preset abnormal rule.

The invention provides an optimized kernel network and an implementation method thereof, and relates to the technical field of kernel networks, the kernel network comprises a fast data channel component XDP arranged on a data link layer; when the network card equipment receives a message data packet, the XDP analyzes and filters the received data packet, or encapsulates or de-encapsulates the received data packet, and modifies a field to forward the data packet; and the XDP matches and filters the received data packet with the rules in the BPF Maps, and discards the data packet when the data packet is illegal. The method comprises the steps that hardware initialization comprises the step of adding a zero copy processing flow when an NAPI polling point processing function is added; the application program configures an XDP socket; the xsk unit executes a BPF instruction, calls a network card driving unit to configure an XSK cache pool, and establishes a DMA mapping relationship between the device and the UMEM shared cache; and the network card drives zero-copy receiving and receiving of the data packet. According to the invention, the kernel network communication efficiency is improved.

The invention discloses a task hierarchical scheduling method for an intelligent computing fusion network, belongs to the technical field of the intelligent computing fusion network, and designs a double-layer task scheduling mechanism (ICCN-DSF) for the intelligent computing fusion network to effectively cope with task scheduling challenges in a large-scale heterogeneous resource environment. Wherein the global task scheduling layer is based on a CIEK-Means algorithm, integrates geographic position constraint and group intelligent optimization, and realizes efficient clustering and dynamic matching of resource ethnic groups; and the local task scheduling layer constructs a three-dimensional state action space and a multi-target reward function through a reinforcement learning algorithm to complete fine-grained resource allocation. According to the method, the scheduling complexity is remarkably reduced, meanwhile, the cross-domain connection requirement is reduced through a layering mechanism, global resource coordination can be achieved only through a small number of WAN links, the operation and maintenance cost and the safety risk are reduced, meanwhile, the cooperation potential of the computing power and the network is fully excavated, and efficient and robust scheduling support is provided for intelligent services in complex scenes.

The invention belongs to the technical field of communication networks, and discloses a block chain topology-consensus co-evolution method and system based on reinforcement learning, and the method comprises the steps: collecting the state information of each node in a block chain network, carrying out the standardization processing and multi-dimensional feature extraction of the state information of each node, and obtaining a block chain topology-consensus co-evolution model; mapping into node state feature vectors available for reinforcement learning, and forming node state codes; a reinforcement learning strategy space is constructed according to the node state codes, a topology evolution strategy is dynamically generated by using a strategy iteration method, and topology adaptive evolution of the block chain network is realized; a structural dynamic constraint mechanism is introduced in the reinforcement learning process, and endogenous driving of topological evolution is carried out; calculating the dynamic difference between the potential energy change between the block chain network nodes and the global structure entropy, establishing an evolution constraint function, and dynamically updating the topological evolution strategy parameters; and the elasticity and the expandability of the network structure are effectively improved.

The invention relates to the technical field of computer networks, and discloses a communication method and device for a computing node, equipment and a storage medium. The method is applied to a computing node, the computing node comprises a virtual switch and a physical network card, a plurality of virtual network interfaces are created in the virtual switch, the plurality of virtual network interfaces are in one-to-one correspondence with a plurality of service networks, and the physical network card is connected with at least one other node. The method comprises the following steps: receiving a target data message of a target service network through a target virtual network interface of a virtual switch; and sending the target data message to a corresponding node in the at least one other node through the physical network card. A plurality of virtual network interfaces are created in the virtual switch, and one virtual network interface corresponds to one service network, so that deployment of a plurality of service networks in the virtual switch is realized, network multiplexing in the virtual switch is realized, and the problem that physical network card resources of computing nodes are insufficient is solved. And a plurality of virtualized networks cannot be provided.

The invention provides an electric power computing network multi-dimensional resource scheduling method, device and platform and a storage medium, and belongs to the technical field of electric power computing power networks, and the method comprises the steps: obtaining the request information of a current service terminal and the computing power resource information of a cloud side computing node; determining an end-to-end time delay constraint, a cloud edge computing power resource constraint and a cloud edge end network bandwidth constraint of the intelligent server; according to the cloud edge computing power unit price and the network bandwidth unit price, determining an objective function of computing network multi-dimensional resource scheduling optimization by taking minimization of the network bandwidth and the cloud edge computing power overhead as an optimization objective; solving the plurality of scheduling constraint models to obtain an optimal solution; and outputting a computing network multi-dimensional resource scheduling strategy according to the optimal solution. According to the method, under the condition that different computing network resource service quality requirements of multiple services are considered, by dynamically deploying multi-dimensional resources such as network bandwidth, cloud computing power and edge computing power, the low response delay requirements of key services such as environmental risks and equipment faults in power grid operation are effectively met, and meanwhile it is ensured that the computing network resource consumption economical efficiency is optimal.

The invention belongs to the technical field of power networks, and particularly relates to a power network vulnerability analysis system and method based on virtual attack and defense deduction, and the system comprises a data collection module which is used for collecting various data of a power network, the various types of data comprise network topology structure data, equipment configuration data, operation state data and security log data; and the threat intelligence integration module is used for collecting and integrating global network security threat intelligence and establishing a data interface with a threat intelligence platform to realize automatic synchronization and updating of the threat intelligence. Through continuous virtual attack and defense deduction, an attack and defense strategy is optimized in combination with a machine learning algorithm, a novel attack means can be simulated, and the power network security state can be monitored in real time. Even if an unprecedented attack mode appears, potential threats can be quickly identified through attack and defense confrontation, the discovery capability of novel and unknown vulnerabilities is greatly improved, and network security risks are responded in time.

The invention provides a dynamic reconstruction optimization method and system for communication information network topology, and relates to the technical field of communication networks, and the method comprises the steps: firstly obtaining node operation dynamic information, link transmission real-time information and network service demand dynamic data of a communication information network; generating a network topology elastic association body containing a plurality of association rules and logics based on the two; inputting the service demand data into a network topology elastic association body to generate a network topology dynamic demand adaptation factor; generating a network topology reconstruction path self-adaptive sequence containing a specific operation instruction and a time sequence based on the network topology dynamic demand adaptation factor and the network topology elastic correlation body; and adjusting a node connection mode and link transmission configuration in a linkage manner according to a network topology reconstruction path self-adaptive sequence, and synchronously updating an association rule to complete dynamic reconstruction optimization. According to the invention, the network stability, reliability and resource utilization rate are improved.

The invention discloses a network protocol integrated development environment system based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an IDE plug-in structure, a protocol analysis engine interface, a context awareness editing module, a user interaction interface and a collaborative view module. According to the method, a development tool is embedded through an IDE plug-in structure, a protocol analysis interface is called to carry out protocol structure identification and semantic modeling, and intelligent suggestions and semantic verification are provided in combination with context information in the protocol editing process. A user can carry out protocol structure editing and visual control through the interactive interface, and different roles can collaboratively carry out protocol design and verification tasks through the collaboration view module. The whole process forms a closed-loop mechanism from protocol modeling and semantic editing to context awareness suggestion, and high-intelligence and high-integration protocol development experience is achieved. The system significantly improves the efficiency and accuracy of protocol development, and is especially suitable for rapid prototype design and standardized development of complex network protocols.

A packet forwarding method, apparatus, and system are provided, and belong to the field of network technologies. A destination address field of a first packet received by a first network node includes a compressed segment identifier corresponding to a first outbound interface or a next-hop node of the first network node; based on the first outbound interface being faulty or the next-hop node being faulty, the first network node determines a second segment identifier based on segment identifier planning information of the node corresponding to the compressed segment identifier, and forwards the first packet based on the second segment identifier, where the second segment identifier is a segment identifier in a segment list of the first packet or a segment identifier in the destination address field.

The invention belongs to the field of Web application technology, XML document processing technology and online editor technology, and discloses an XML semantic editing system based on an aviation knowledge graph. The system comprises a front-end application module, an XML processing engine module, a DTD rule verification module, a visual editing module, a plug-in extension module, a collaborative editing module and an aviation knowledge graph integration module. According to the method, professional and efficient editing of XML documents in the aviation field is achieved through the full-process design of front-end interaction, XML processing, DTD verification, visual editing, semantic assistance and collaborative management, and the Web technology, the XML processing technology, the DTD verification technology, the knowledge graph technology and the collaborative editing technology are integrated, so that the XML documents in the aviation field are edited in a professional and efficient mode. The problems that an existing XML editing tool is difficult to deploy, poor in compliance, low in efficiency and weak in cooperation in the aviation maintenance field are solved, and a specialized and efficient XML semantic editing scheme is provided for the aviation maintenance industry.

The invention discloses an SRv6 computing power network path optimization method and system based on multi-dimensional dynamic scoring, and belongs to the technical field of communication networks, and the method comprises the steps: building a multi-dimensional dynamic scoring system of load scoring, delay scoring and service priority scoring through collecting node loads, link congestion, geographic distances, topology hops and service types in real time; the method comprises the following steps: dynamically selecting an optimal path based on a DMPSC-T table (including a LastUpdate Time / ExpireTime timestamp mechanism); and when a better path is detected, an End.Redit instruction newly defined by SRv6 is utilized to trigger SID dynamic replacement: an Endpoint node directly replaces a target SID in a SegmentList, and a transfer node generates an ACL rule through a PBR to realize redirection. According to the invention, millisecond-level path switching can be realized, the service quality of high-priority business is effectively improved, and the global scheduling efficiency of network resources is optimized.

The invention relates to the technical field of unmanned aerial vehicle group networks, in particular to a dynamic clustering routing method for a high-dynamic unmanned aerial vehicle group network, which is characterized by comprising the following steps of: dividing the whole unmanned aerial vehicle group network into a centralized-distributed hierarchical domain architecture, dividing the network into a plurality of clusters, and enabling each cluster to consist of a cluster head and a plurality of cluster members, the cluster head can be recombined into a higher-level cluster; according to the method, a layered and domain-divided network architecture is provided, cluster heads are dynamically elected in combination with a grey wolf optimization algorithm, real-time self-adaptive clustering and load balancing routing of the unmanned aerial vehicle group in a high-speed mobile environment are realized through a double-cluster-head switching and reselection mechanism, the cluster heads and paths are ensured to be optimal, routing is optimized through a genetic algorithm, relay forwarding is reduced, and the routing efficiency is improved. The communication overhead is reduced, the service life of the network is prolonged, the robustness of the system is enhanced by the alpha-beta-delta leader model and the iterative surrounding strategy, the time delay is reduced and the transmission success rate is improved by the fuzzy clustering, and the real-time reliable communication requirement in a high dynamic scene is met.

The invention belongs to the technical field of nuclear power station maintenance management, and particularly relates to a nuclear power maintenance decision-making system and method based on multi-Agent cooperation. The system comprises an input layer, a multi-Agent cooperation layer, a knowledge support layer, a decision processing layer, an output and interaction layer and a feedback learning layer. The input layer receives initial work order information including equipment basic information and fault description; the multi-Agent collaboration layer allocates sub-tasks to predefined six types of professional Agents according to work order information and completes information interaction; the knowledge support layer comprises a nuclear power professional knowledge base, a historical maintenance database and a rule and regulation library; the decision processing layer performs conflict detection, negotiation and decision fusion on Agent output; the output and interaction layer provides a decision result display and man-machine interaction interface; and the feedback learning layer realizes comprehensive improvement of nuclear power maintenance decision-making efficiency and safety. The method has the beneficial effects that a multi-professional Agent collaborative network technical means is adopted, and the technical effects of maintenance decision cross-professional information instant sharing and efficient collaboration are realized.

The invention relates to the technical field of unmanned aerial vehicle fault detection, in particular to an unmanned aerial vehicle flight control system abnormity tracing method based on a deep matching network. An abnormal knowledge graph containing entities and semantic relations is constructed through the preprocessed multi-source heterogeneous data, and abnormal inducements are mapped into inducement label vectors through a graph encoder; a flight control state anomaly representation vector is generated through the depth time sequence feature extraction network, and anomaly is detected; when an anomaly is detected, calculating a correlation score of an anomaly characterization vector and an inducement label vector through a deep matching network, and screening first K candidate inducements; and then taking the candidate cause nodes as source points in the knowledge graph, performing deep search according to a preset path to construct candidate cause and effect paths, performing sorting through a node correlation scoring mechanism, and outputting interpretable traceability paths. According to the method, based on a deep matching network technology, the accuracy and interpretability of anomaly detection and traceability in a complex environment are improved, and efficient and accurate anomaly inducement matching and causal path reasoning are realized.

The invention discloses a method and system for communication through a unified communication slot, and relates to the technical field of intelligent communication networks, and the method comprises the steps that the communication slot receives heterogeneous protocol data streams in real time, parses protocol grammar structures and semantic features of the heterogeneous protocol data streams in parallel through two channels, fuses the protocol grammar structures and the semantic features, generates PIR vectors, and sends the PIR vectors to a server; acquiring broadcast information and dynamic routing update messages of adjacent equipment in real time, and generating a real-time topology state library; and on the basis of a PIR vector, a delay sensitivity coefficient and a fault-tolerant threshold parameter are extracted, a quantum optimization model is constructed in combination with a real-time topology state library, a path with the minimum comprehensive transmission cost is calculated, physical address mapping, protocol compression packaging and service index verification are carried out, and a simplified quantum routing tag is generated. Unified semantic representation of heterogeneous protocols is realized through dual-channel protocol analysis and feature fusion, and high-timeliness secure transmission is realized through quantum optimization routing and dynamic encryption binding.

The invention discloses an AI large model-oriented financial private network optimization method and system, and relates to the technical field of communication networks. According to the method, an exclusive path strategy is generated for AI training, reasoning and sensitive data traffic by collecting AI service requirements and network states and utilizing the SID programming capability of SRv6; the load of the computing power node is monitored in real time, the computing power state is linked with network scheduling, and network-computing power collaborative optimization is realized; a hop-by-hop path authentication mechanism based on a dynamic authentication segment identifier Auth-SID is introduced, so that the security of a data transmission path is enhanced; and end-to-end visual operation and maintenance and closed-loop feedback of the service flow are realized by adopting a flow-following detection technology. According to the invention, the problems of mismatching of flow scheduling and AI service requirements, insufficient network and computing power collaboration, lack of path security guarantee and weak operation and maintenance visualization capability in the prior art are solved, deep adaptation of network resources and the AI service requirements is realized, and the computing power collaboration efficiency, the path security and the operation and maintenance intelligence level are improved.